MR elastography (MRE) involves measuring motion resulting from low frequency vibration. Present MR elastography methods use a separate gradient waveform to encode the motion, for example, in the context of the Larmor equation that is used to measure tissue strain and discussed in U.S. Pat. No. 5,952,828 issued to Rossman et al. The gradient waveform may be added between the RF excitation and the readout of the echo. The resulting increased echo time has the undesirable effect of decreasing the signal amplitude, as well as increasing the imaging time.
MRE has shown promise in tissue imaging, including breast imaging. Several acquisition methods with corresponding reconstruction methods have been used to find the shear modulus of tissue in vivo. The first elastographic methods used ultrasound to measure static and dynamic displacements and the raw strain images were interpreted without reconstruction. See J. Ophir et al., “Elastography: A Quantitative Method for Imaging the Elasticity of Biological Tissues,” Ultrasonic Imaging, 13:111-134 (1991); and K. J. Parker et al., “Tissue response to mechanical vibrations for ‘sonoelasticity imaging,’” Ultrasound Med. Biol. 16(3):241-6(1990). The first MR elastographic method measured the local wavelengths of plane waves that were measured with a phase contrast method to ascertain the shear modulus. Since then, static MR methods have also been developed. More recently, methods have been developed that measure steady state motion instead of plane wave motion and use reconstructions of the partial differential equations for dynamic elastic motion.
All present MR-based methods use similar phase contrast methods to encode the motion of the tissue resulting from the low frequency vibrations induced in the tissue. Phase data of each voxel, i.e., a 3D pixel depicted as a 2D pixel with color/grey scale amplitude indications, is accumulated by moving the tissue in synchrony with the motion-encoding gradients. In static MR methods, the accumulated phase of each voxel reflects the amplitude of the motion. In dynamic MR methods, the accumulated phase of each voxel reflects the phase and amplitude of the tissue motion such that the accumulated phase must be acquired for several relative phases between the motion and gradients to solve for the amplitude and phase of the motion of each voxel.
All of the methods described above employ separate motion encoding gradients to accumulate the phase in each voxel.
Current methods for breast cancer detection and diagnosis are imperfect. For women under the age of 40 and for those under the age of 50 but with radiographically dense breasts, physical breast examination is the primary method of general screening. Unfortunately, physical breast examination has very low sensitivity and detects less than 20% of breast cancers that are detectable by X-ray mammography. In addition, cancers detected by physical exams tend to be at a later stage than those evident on mammographs, adversely affecting their prognosis. For younger women with dense breasts, the rates of false negatives and false positives generated by physical breast exams are even higher.
X-ray mammography has become the norm for breast cancer screening in recent years. However, X-ray mammography not only exposes subjects to ionizing radiation, but also has limited sensitivity and low positive predictive value. Conventional mammography also suffers from patient acceptance issues due to compression-related discomfort. While mammography is regarded as the single most important tool in early detection of breast cancer, it is not generally recommended for women under the age of 40 due to its limited efficacy on pre-menopausal breasts.
Thus, while contemporary screening practices have a beneficial effect on breast cancer detection, the limitations delineated above, especially among younger women, underscore the need to develop alternative methods to detect and characterize breast cancer. Many alternative strategies for breast cancer detection are currently being developed. Among them, a number of strategies for imaging the breast with microwaves are being investigated at the simulation, phantom and clinical scales. One approach maps microwave absorption by recording the thermoacoustic response induced by microwaves. In these studies, the microwave power absorbed by tissues generates heat and causes thermal expansion of the tissues, which launch pressure waves detectable by ultrasonic transducers. Results from these studies have shown millimeter spatial resolution arising from microwave irradiation at the centimeter wavelength scale. Although ultrasound detection has the advantages of wide-band response and relatively low cost, it also has considerable drawbacks, such as signal loss from attenuation, background clutter and geometric dilution resulting from the propagation distance between the target and the remotely-positioned noninvasive sensors. Alternative approaches to image the breast through non-thermally induced mechanical waves detected by ultrasonic transducers have also been investigated since the early 1990s.
In addition to ultrasonic techniques, MR methods have also been applied to detect non-thermally induced elastic waves emitted by tissues. While traditional MRI does not work well for detecting breast cancers, due to the low contrast between normal and malignant tissues, recent reports on the detection of motion-induced mechanical waves using MR techniques demonstrate the superior volumetric resolution of MR and the potential benefit of applying MR in breast cancer detection. In these studies, MR techniques are employed to record an elastic wave response and map tissue elasticity, which provide better discrimination of malignant tissues with altered electrical properties. Despite these potential advantages, MR techniques have not been applied to measure thermally-induced mechanical waves generated by microwave power absorption.
One problem inherent in thermoelastic wave induction is that the process is governed by local power absorption which in the electromagnetic case is a product of the intrinsic tissue properties (i.e., electrical conductivity) and the squared magnitude of the electric field. The time-averaged (or instantaneous) power deposition is a function of the fundamental property of the tissue, but also of extrinsic factors which shape specifics of the applied field distribution. For example, the geometry of the breast, the characteristics of the microwave radiator, and the electrical properties of both normal and pathological (if any) tissues govern the local field behavior. This problem has not been overcome in the art, and a continuing need exists to develop new systems for breast cancer detection that are safer, more effective and more comfortable than current detection tools.